Tables in Python
How to make tables in Python with Plotly.
New to Plotly?
Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.
go.Table
provides a Table object for detailed data viewing. The data are arranged in
a grid of rows and columns. Most styling can be specified for header, columns, rows or individual cells. Table is using a column-major order, ie. the grid is represented as a vector of column vectors.
Note that Dash provides a different type of DataTable.
Basic Table¶
import plotly.graph_objects as go
fig = go.Figure(data=[go.Table(header=dict(values=['A Scores', 'B Scores']),
cells=dict(values=[[100, 90, 80, 90], [95, 85, 75, 95]]))
])
fig.show()
Styled Table¶
import plotly.graph_objects as go
fig = go.Figure(data=[go.Table(
header=dict(values=['A Scores', 'B Scores'],
line_color='darkslategray',
fill_color='lightskyblue',
align='left'),
cells=dict(values=[[100, 90, 80, 90], # 1st column
[95, 85, 75, 95]], # 2nd column
line_color='darkslategray',
fill_color='lightcyan',
align='left'))
])
fig.update_layout(width=500, height=300)
fig.show()
Use a Pandas Dataframe¶
import plotly.graph_objects as go
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2014_usa_states.csv')
fig = go.Figure(data=[go.Table(
header=dict(values=list(df.columns),
fill_color='paleturquoise',
align='left'),
cells=dict(values=[df.Rank, df.State, df.Postal, df.Population],
fill_color='lavender',
align='left'))
])
fig.show()
Tables in Dash¶
Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash
, click "Download" to get the code and run python app.py
.
Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.
Sign up for Dash Club → Free cheat sheets plus updates from Chris Parmer and Adam Schroeder delivered to your inbox every two months. Includes tips and tricks, community apps, and deep dives into the Dash architecture. Join now.
Changing Row and Column Size¶
import plotly.graph_objects as go
values = [['Salaries', 'Office', 'Merchandise', 'Legal', '<b>TOTAL<br>EXPENSES</b>'], #1st col
["Lorem ipsum dolor sit amet, tollit discere inermis pri ut. Eos ea iusto timeam, an prima laboramus vim. Id usu aeterno adversarium, summo mollis timeam vel ad",
"Lorem ipsum dolor sit amet, tollit discere inermis pri ut. Eos ea iusto timeam, an prima laboramus vim. Id usu aeterno adversarium, summo mollis timeam vel ad",
"Lorem ipsum dolor sit amet, tollit discere inermis pri ut. Eos ea iusto timeam, an prima laboramus vim. Id usu aeterno adversarium, summo mollis timeam vel ad",
"Lorem ipsum dolor sit amet, tollit discere inermis pri ut. Eos ea iusto timeam, an prima laboramus vim. Id usu aeterno adversarium, summo mollis timeam vel ad",
"Lorem ipsum dolor sit amet, tollit discere inermis pri ut. Eos ea iusto timeam, an prima laboramus vim. Id usu aeterno adversarium, summo mollis timeam vel ad"]]
fig = go.Figure(data=[go.Table(
columnorder = [1,2],
columnwidth = [80,400],
header = dict(
values = [['<b>EXPENSES</b><br>as of July 2017'],
['<b>DESCRIPTION</b>']],
line_color='darkslategray',
fill_color='royalblue',
align=['left','center'],
font=dict(color='white', size=12),
height=40
),
cells=dict(
values=values,
line_color='darkslategray',
fill=dict(color=['paleturquoise', 'white']),
align=['left', 'center'],
font_size=12,
height=30)
)
])
fig.show()
Alternating Row Colors¶
import plotly.graph_objects as go
headerColor = 'grey'
rowEvenColor = 'lightgrey'
rowOddColor = 'white'
fig = go.Figure(data=[go.Table(
header=dict(
values=['<b>EXPENSES</b>','<b>Q1</b>','<b>Q2</b>','<b>Q3</b>','<b>Q4</b>'],
line_color='darkslategray',
fill_color=headerColor,
align=['left','center'],
font=dict(color='white', size=12)
),
cells=dict(
values=[
['Salaries', 'Office', 'Merchandise', 'Legal', '<b>TOTAL</b>'],
[1200000, 20000, 80000, 2000, 12120000],
[1300000, 20000, 70000, 2000, 130902000],
[1300000, 20000, 120000, 2000, 131222000],
[1400000, 20000, 90000, 2000, 14102000]],
line_color='darkslategray',
# 2-D list of colors for alternating rows
fill_color = [[rowOddColor,rowEvenColor,rowOddColor, rowEvenColor,rowOddColor]*5],
align = ['left', 'center'],
font = dict(color = 'darkslategray', size = 11)
))
])
fig.show()
Row Color Based on Variable¶
import plotly.graph_objects as go
import pandas as pd
colors = ['rgb(239, 243, 255)', 'rgb(189, 215, 231)', 'rgb(107, 174, 214)',
'rgb(49, 130, 189)', 'rgb(8, 81, 156)']
data = {'Year' : [2010, 2011, 2012, 2013, 2014], 'Color' : colors}
df = pd.DataFrame(data)
fig = go.Figure(data=[go.Table(
header=dict(
values=["Color", "<b>YEAR</b>"],
line_color='white', fill_color='white',
align='center', font=dict(color='black', size=12)
),
cells=dict(
values=[df.Color, df.Year],
line_color=[df.Color], fill_color=[df.Color],
align='center', font=dict(color='black', size=11)
))
])
fig.show()
Cell Color Based on Variable¶
import plotly.graph_objects as go
from plotly.colors import n_colors
import numpy as np
np.random.seed(1)
colors = n_colors('rgb(255, 200, 200)', 'rgb(200, 0, 0)', 9, colortype='rgb')
a = np.random.randint(low=0, high=9, size=10)
b = np.random.randint(low=0, high=9, size=10)
c = np.random.randint(low=0, high=9, size=10)
fig = go.Figure(data=[go.Table(
header=dict(
values=['<b>Column A</b>', '<b>Column B</b>', '<b>Column C</b>'],
line_color='white', fill_color='white',
align='center',font=dict(color='black', size=12)
),
cells=dict(
values=[a, b, c],
line_color=[np.array(colors)[a],np.array(colors)[b], np.array(colors)[c]],
fill_color=[np.array(colors)[a],np.array(colors)[b], np.array(colors)[c]],
align='center', font=dict(color='white', size=11)
))
])
fig.show()
Reference¶
For more information on tables and table attributes see: https://plotly.com/python/reference/table/.
What About Dash?¶
Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.
Learn about how to install Dash at https://dash.plot.ly/installation.
Everywhere in this page that you see fig.show()
, you can display the same figure in a Dash application by passing it to the figure
argument of the Graph
component from the built-in dash_core_components
package like this:
import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )
from dash import Dash, dcc, html
app = Dash()
app.layout = html.Div([
dcc.Graph(figure=fig)
])
app.run_server(debug=True, use_reloader=False) # Turn off reloader if inside Jupyter